Research Grid (R.grid) launches new Site Feasibility solution to accelerate trial startups and expand global patient access
The tool uses real-world data paired with Research Grid's proprietary network of over 97,000 communities
A process that once took six months can now be done in minutes thanks to this new technology

LONDON and NEW YORK, Aug. 6, 2025 /PRNewswire/ -- Research Grid, a leader in AI automation of clinical trials, today unveiled its new global Site Feasibility solution that helps trial sponsors and CROs to quickly find, assess, and activate the best sites for their studies. The Site Feasibility tool is powered by real-world data and Research Grid's proprietary network of over 400 million people across 157 countries and 2,000 medical indications, as well as thousands of trial sites globally highlighting their facilities and trials. With it, sponsors receive instant, protocol-specific insights that cut start-up delays, boost recruitment, and support more inclusive trial planning.

The Challenge: Feasibility is Broken

Feasibility remains one of the most common bottlenecks in clinical research, with site selection and activation typically taking up to 6 months due to manual oversight, outdated site data, and inconsistent response rates:

80% of trials miss enrollment deadlines
Over 30% of sites under-enroll, 11% fail to recruit a single patient
85% of studies require costly timeline extensions due to recruitment delays
Sites can spend up to 4,500 hours annually on feasibility processes

"Site feasibility has long been a major cause of delay and inequity in clinical research," said Dr. Amber Hill, founder and CEO of Research Grid. "We're showing that with the right AI tech, trials can be safely admin-free. That's not just a workflow improvement. It means life-saving treatments are more likely to succeed in trials and reach the people who need them, faster."

Research Grid's Site Feasibility Solution

Research Grid's new solution tackles these challenges head-on, matching protocol needs with real-world patient and infrastructure access, automating the process from outreach to activation.

Global Patient Reach: Access a proprietary network of 96,000+ verified communities across 157 countries, matched to protocol-specific criteria.
Accelerated Planning: Replace weeks of manual outreach with instant AI-powered feasibility reports and auto-scored site surveys.
Equity-Driven Design: Identify underrepresented regions and sites that support inclusive, representative enrollment.
Improved Recruitment: Prioritize sites with real access to eligible patients, not just historical performance metrics.
Unified Workflow: Plan, compare, and track feasibility activities across global teams in one streamlined platform.

The Site Feasibility Solution is available now, either as a self-service tool or a fully managed service, providing flexibility for feasibility on a single study or across an entire global portfolio.

This launch continues Research Grid's pioneering work to replace outdated manual processes with intelligent automation--making clinical trials faster, smarter, and more inclusive globally.

About Research Grid

Research Grid is the automation engine for admin-free clinical trials. Far too many trials fail because of delays, errors, or weak patient engagement caused by legacy software and manual processes. Our mission is to enable faster, more successful clinical trials by engineering smart software that safely automates back-office admin across the full life cycle. Informed by deep expertise and first-hand experience, we have built comprehensive solutions for patient and community engagement (Inclusive) and clinical trial management (TrialEngine) that support a variety of trial types and therapeutic areas. Founded in 2020 by Dr Amber Hill, Research Grid is headquartered in London and has raised a total of $8 million in venture funding to date.

View original content:https://www.prnewswire.co.uk/news-releases/clinical-trial-site-feasibility-from-6-months-to-minutes-with-research-grids-new-automation-tool-302523485.html

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